value now. value over time. © copyright 2010, osisoft, llc all rights reserved. enabling data...
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Value now. Value over time. © Copyright 2010, OSIsoft, LLC All rights Reserved.
Enabling Data Infrastructure for Utility Sustainability
John Lacy
November 8, 2010
2 Value Now - Fast, Simple, Sustainable © 2010 OSIsoft, LLC. All rights reserved
Enabling Smart Grid components
1) Generation
2) Transmission & Distribution
3) Meters
4) Hardware
5) Consumers
6) Smart Infrastructure
Smart
Smart
Smart
Smart
Smart
– “The Enabler”
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Data, Data, Data and more Data
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Meter Data Volumes – Yesterday, Today, and Tomorrow.
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Beyond AMI: Example Data Flows
AMRPI
C&IInterval
AMIn
(Future)
MeteredFeeder Data
SCADA1-n
OMS
DMS
Second orSub-second
30 minutecollected hourly
30 minutecollected hourly
GISMobile
DispatchWMS
Feeder Amps and other SCADA Data
Circuit Analysis Tool
Distribution Planning
daily readscollected daily
5 minute reads continuously
15 minute/hourly
5 minute/hourly
Access to all data
Distribution Operations
Access to all data
Field Engineering
Access to all data
Asset Information
Near -real timetransformer kW, device loading, voltages, etc.
15 minute/hourly
Manual Substation
Reads
Monthly
HAN
15 minutecollected daily Asset Management/
Substations
Access to all data CBM
Multi-year history and reporting flexibility for analysis such as: PF/Voltage/Var DG Loss Load
Multi-year history and real and near real-time data for: Capacitor Operations DG Status
Multi-year history and real and near real-time data for: PF/Voltage/Var Analysis Capacitor Operations
Source devices will evolve with new technologies and
cost effectiveness
Various data granularity and delivery frequencies
that will increase over time
CIS Accounting
Financial Systems of Record
(data streams not included in this
scenario)
IED
Capacitor Control System
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Smart Infrastructure - “The Enabler”
• DATA MANAGEMENT INFRASTRUCTURE is ESSENTIAL
• Need a home for all this data – accessible & highly available
• Underpins and supports the entire Smart Grid
• Connectivity to disparate devices and data sources
• Data collection at original resolution – milliseconds to minutes
• Liberate data from secure, locked down proprietary systems
• Data analysis – ad hoc, event based, in real time
• Transformation to information for decision support
• Scalable – to millions of meters and values
• Extensible – to other databases, applications
• Communications – robust, fast, bidirectional
7
Smart Generation
• Multiple Control systems’ data aggregated to improve unit and plant performance
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Phase Angle Jumping - Grid Stability
5:00 PM 5:10 PM
Phase Angle difference Continuing to grow.
60⁰
120⁰
Diff
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Substation Dashboard Level 3 – Asset View
Value Propositions
1. Turbine Manufacturer Warranty Management– “Fox Watching the Hens”– “Bathtub Curve” Implications for LTSA Concept– Need: Focus on Top-Ten Sources
2. Increasing kWh produced – Wind Farm Operations– Turbine Availability– Turbine Operating Efficiency
3. Increasing value of kWh produced – Utility Operations– Improving utility integration (forecasting and scheduling)– Improving market value of power (real-time info to power
marketing/trading floor)– VAR/Grid Stability Management
4. “Intangibles” – Corporate Requirements– Enterprise Integration,– Separation of Process Control Network from User/Enterprise– Regulatory & Reporting– Technology Risk Management – Perception and Reality
Asset Management Value PropositionTurbine Production Example
HoursTurbineClass
(kW)Capacity
Factor AvailabilityAnnual Expected
Output (kWh)*
BusbarPrice/kWh
Annual CashFlow per WTG
8760 600 33% 100% 1,734,480 0.0425 $ 73,715.40
8760 1000 33% 100% 2,890,800 0.0425 $ 122,859.00
8760 1500 33% 100% 4,336,200 0.0425 $ 184,288.50
8760 2000 33% 100% 5,781,600 0.0425 $ 245,718.00
8760 2500 33% 100% 7,227,000 0.0425 $ 307,147.50
8760 5000 33% 100% 14,454,000 0.0425 $ 614,295.00
*Formula = Hours * Generator Capacity * Capacity Factor * Availability
•A typical utility scale wind farm may have 30 to 200 Turbines•Large owners (e.g. Iberdrola – 3500MWs) may have thousands of turbines•A single percentage point gain/loss of “in-market” availability (e.g. turbines available to operate when the wind is blowing) for
•Iberdrola Total Fleet would result•in a 1st Year ROI/loss of $4.3MUSD. •NPV over 5 Years = $13.5MUSD @ 18% Discount Rate•Based on US prices, power rate in Spain is .07 to .10/kWh produced
•For a Single Wind Farm of 150MWs:•In a 1st year ROI of $185,000•NPV over 5 years = $576,000 @ 18% Discount Rate
Geographic Status map:
• Color-coded•“Rollovers” showing windspeed & project output, # of faulted turbines or state change• Project drill down capability
Defined KPIs per region/project, color coded with drill down capability:
• Financial• Production• Operations
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“Roll-up” Mechanism: Net KWh Roll-Up
Load on meter data
All AMI meters summed to one distribution transformer
All distribution transformers summed to circuit segment
Circuit segment summed up to feeder
Total feeders summed to sub
• Key Points• Each trend shown is aggregated load (kWh) up to the next higher
trend from an individual meter, transformer, line segment, breaker and sub.
• If you overlay the Distribution SCADA load, the difference would be losses or leakage
• The physical model (CIM) allowing the aggregation and roll-up of individual loads
• End to end visibility – integrating meter and distribution system(s) operational data
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Utility Landscape